Building model generation and intelligent light control for smart windows

ABSTRACT

A smart window system is provided. The system includes a plurality of smart windows, each having at least one electrochromic window and a plurality of sensors. The system includes a control system coupling the plurality of smart windows and the plurality of sensors. The control system is configured to couple to a network, and configured to generate a building model that includes information regarding the plurality of smart windows and is based on information from the plurality of sensors and information from the network.

BACKGROUND

Electrochromic devices, in which optical transmissivity is electricallycontrolled, are in current usage in building windows and in dimmableautomotive rearview mirrors. Generally, electrochromic windows for abuilding are controlled with a driver and a user input, e.g., a dimmercontrol. Electrochromic rearview mirrors in automotive usage often havea light sensor aimed to detect light from headlights of automobiles, andare user-settable to engage an auto-dim function that adjusts the tintof the mirror based on input from the light sensor. There is a need inthe art for a control system for electrochromic devices which goesbeyond such basic settings and functions.

SUMMARY

In some embodiments, a smart window system is provided. The systemincludes a plurality of smart windows, each having at least oneelectrochromic window and a plurality of sensors. The system includes acontrol system coupling the plurality of smart windows and the pluralityof sensors. The control system is configured to couple to a network, andconfigured to generate a building model that includes informationregarding the plurality of smart windows and is based on informationfrom the plurality of sensors and information from the network.

In some embodiments, a smart window system is provided. The systemincludes a plurality of smart windows, each smart window of theplurality of smart windows having integrated into the smart window atleast one sensor and at least one electrochromic window. The systemincludes a control system that includes the plurality of smart windowsand is configured to couple to a network. The control system isconfigured to produce a building model based on information from thenetwork and based on information from sensors of the plurality of smartwindows, wherein the building model includes information regardingplacements of the plurality of smart windows relative to a building.

In some embodiments, a method of operating a smart window system,performed by one or more processors of the smart window system isprovided. The method includes receiving sensor information from sensorsof the smart window system, wherein the smart window system includes aplurality of smart windows with electrochromic windows, and the sensors.The method includes receiving information from a network and generating,in the smart window system, a building model referencing each smartwindow of the plurality of smart windows with placement, location ororientation of the smart window, wherein at least a portion of thebuilding model is based on the sensor information and the informationfrom the network. The method includes controlling each smart window ofthe plurality of smart windows, based on the building model.

Other aspects and advantages of the embodiments will become apparentfrom the following detailed description taken in conjunction with theaccompanying drawings which illustrate, by way of example, theprinciples of the described embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The described embodiments and the advantages thereof may best beunderstood by reference to the following description taken inconjunction with the accompanying drawings. These drawings in no waylimit any changes in form and detail that may be made to the describedembodiments by one skilled in the art without departing from the spiritand scope of the described embodiments.

FIG. 1 is a system diagram of a smart window system that has adistributed device network control system architecture in accordancewith an embodiment of the present disclosure.

FIG. 2 is a system diagram of a smart window that has an electrochromicwindow and a window frame with an embedded module.

FIG. 3 is a system diagram of an intelligent window controller/driver,from the smart window system of FIG. 1.

FIG. 4 is a system diagram of a command and communication device, fromthe smart window system of FIG. 1.

FIG. 5 is a block diagram showing aspects of the distributed devicenetwork control system architecture of FIG. 1.

FIG. 6A shows aspects of a building model that can be used inembodiments of the smart window system.

FIG. 6B shows aspects of a shade model that can be used in embodimentsof the smart window system.

FIG. 6C shows aspects of a temperature model that can be used inembodiments of the smart window system.

FIG. 6D shows a light and comfort model that can be used in embodimentsof the smart window system.

FIG. 6E shows a comparison engine that can be used in embodiments of thesmart window system.

FIG. 6F shows the building model of FIG. 6A in the distributed devicenetwork of FIGS. 1 and 5, which could also include some or all of themodels of FIGS. 6B-6D and the comparison engine of FIG. 6E, in variousembodiments.

FIG. 7 depicts a data structure suitable for holding the building modeland other models and comparison engine of FIGS. 6A-6F in the distributeddevice network with smart windows.

FIG. 8 is a system diagram of the server of FIG. 1, with various modulesand repositories, as suitable for use with smart window systems.

FIG. 9 is a system diagram of the distributed device network of FIGS. 1,5 and 6F interacting with smart windows and lights, in a cooperativesystem with voting and visual representation for users of a smart windowsystem.

FIG. 10 shows an embodiment of a smart window with transmissivitygradation.

FIG. 11 shows an embodiment of a smart window with a motorized windowblind and motorized opening and closing.

FIG. 12 shows an embodiment of a smart window with an auto-tintfunction.

FIG. 13 shows an embodiment of a smart window system with voice controland a nearest window location function.

FIG. 14 depicts a building with a smart windows pattern.

FIG. 15 is a flow diagram of a method of operating a smart windowsystem.

FIG. 16 is an illustration showing an exemplary computing device whichmay implement the embodiments described herein.

DETAILED DESCRIPTION

A smart window system, disclosed herein, has a distributed devicenetwork control system architecture that can distribute control ofoptical transmissivity of smart windows across the smart windows,intelligent window controller/drivers, a command and communicationdevice, and one or more resources on a network. The smart window systemcombines input from sensors integrated with the smart windows, userinput, and information and direction from the network to control thesmart windows in an interactive, adaptive manner. Control can shift fromone component to another, be shared across multiple components, or beoverridden by one component of the system, in various embodiments. Thedistributed nature of the architecture and the control support varioussystem behaviors and capabilities. Some embodiments of the smart windowsystem develop a building model, with shade modeling for the smartwindows. Various embodiments of smart windows and operating scenariosfor smart window systems are described herein.

FIG. 1 is a system diagram of a smart window system that has adistributed device network control system architecture in accordancewith an embodiment of the present disclosure. The system is both modularand distributed, and is suitable for installation in various living,working or commercial spaces, such as an apartment, house, an office, abuilding, a store, a mall, etc. Modularity allows for replacement ofindividual components, upgrades, expansion, linking of two or moresystems, and communication in the system and among multiple systems.Wireless couplings, wired couplings, and combinations thereof aresupported by the smart window system. Although antennas 124 are shownfor the wireless coupling, further embodiments could use infraredcoupling.

Control is distributed across one or more first control systems 114,with one in each smart window 102, one or more second control systems116, with one in each intelligent window controller/driver 104, a thirdcontrol system 118 in a command and communication device 106, and afourth control system 120 in a server 108 coupled to a network 110. Eachsmart window 102 has an antenna 124 and is thereby wirelessly connectedto a nearby intelligent window controller/driver 104, also with anantenna 124. In further embodiments, a wired connection could be used.Each intelligent window controller/driver 104 is wirelessly connected tothe command and communication device 106, which has an antenna 124. Infurther embodiments, a wired connection could be used. The command andcommunication device 106 is coupled to a network 110, such as the globalcommunication network known as the Internet. This coupling could be madevia a wireless router (e.g., in a home, office, business or building),or a wired network connection. User devices 136 (e.g., smart phones,computers, various computing and/or communication devices) can couple tothe command and communication device 106, for example by a directwireless connection or via the network 110, or can couple to the server108 via the network 110, as can other systems 138 and big data 112. Insome embodiments, the server 108 hosts an application programminginterface 140. The server 108 could be implemented in or include, e.g.,one or more physical servers, or one or more virtual servers implementedwith physical computing resources, or combinations thereof.

Modularity of the system supports numerous layouts and installations.For example, each windowed room in a building could have one or moresmart windows 102 and a single intelligent window controller/driver 104for that room. An intelligent window controller/driver 104 could controlsmart windows 102 in part of a room, an entire room, or multiple rooms.The intelligent window controller/driver(s) 104 for that floor of thebuilding, or for a portion of or the entire building in someembodiments, could tie into a single command and communication device106, which is coupled to the network 110 and thereby coupled to theserver 108. In a small installation, one or more smart windows 102 couldcouple to a single intelligent window controller/driver 104 for localdistributed control, or a single command and communication device 106for both local and network distributed control. Or, an intelligentwindow controller/driver 104 could be combined with the command andcommunication device 106, in a further embodiment for small systems thatuse both local control and network information. Large systems, e.g., formultiple occupant buildings, could have multiple command andcommunication devices 106, e.g., one for each occupant or set ofoccupants, or each floor or level in the building, etc. Upgrades orexpansions are readily accommodated by the addition of furthercomponents according to the situation.

In one embodiment as shown in FIG. 1, the command and communicationdevice 106 has a wireless interface 128, a wired interface 130, acontrol system 118, a rules engine 132, a network interface 134, and auser I/O (input/output) module 142. The wireless interface 128 and/orthe wired interface 130 are used for coupling to the intelligent windowcontroller/driver(s) 104. The network interface 134 is used forconnecting to the network 110. For example, the network interface 134could connect to a wireless router or Wi-Fi, e.g., via the wirelessinterface 128, or to a wired network via the wired interface 130. Insome embodiments, the wireless interface 128 and/or the wired interface130 can couple to third-party devices for sensing, input and/or output(see, e.g., description regarding FIG. 3). The rules engine 132 usesinformation from the network 110, which can include direction from thefourth control system 120 in the server 108, and can include informationfrom user devices 136, other systems 138, or big data 112, to create,populate, modify, or adapt various rules for operation of the smartwindows 102. The user I/O module 142 accepts user input, e.g., viabuttons, a touchscreen, etc., and displays user output, e.g., via adisplay screen or with LEDs or other lamps, etc. Some embodiments maylack the user I/O module 142, or have a user input module or an outputmodule. In keeping with the nature of this distributed control system,the third control system 118 of the command and communication device 106can direct operation of the smart windows 102, the second control system116 of the intelligent window controller/driver(s) 104 can directoperation of the smart windows 102, the fourth control system 120 of theserver 108 can direct operation of the smart windows 102, and/or thefirst control system 114 of each smart window 102 can direct operationof that smart window 102, in various combinations. Some embodiments havea failover mechanism, in which control and/or communication are routedaround a failed device in the system.

As shown by the dashed lines, communication can proceed amongst variousmembers of the smart window system over various paths, in variousembodiments. In some embodiments, a message or other communication ispassed along a chain, such as from a smart window 102, to an intelligentwindow controller/driver 104, or via the intelligent windowcontroller/driver 104 to the command and communication device 106, andvice versa. In some embodiments, a device can be bypassed, either bydirect communication between two devices or by a device acting as arelay. For example, a smart window 102 could communicate directly with acommand and communication device 124 wirelessly via the wirelessinterface 128 or via the wired interface 130. Or, an intelligent windowcontroller/driver 104 could relay a message or other communication, ascould the command and communication device 106. In some embodiments,messages or communications can be addressed to any component or devicein the system, or broadcast to multiple devices, etc. This could beaccomplished using packets for communication, and in some embodimentsany of the control systems 114, 116, 118, 120 can communicate with thecloud, e.g., the network 110.

FIG. 2 is a system diagram of a smart window 102 that has anelectrochromic window 204 and a window frame 202 with an embedded module206. The embedded module 206 could be positioned at the bottom, top, toone or both sides, or distributed around the window frame 202 in variousembodiments. The embedded module 202 has one or more sensors 212, whichcould include temperature, light, audio/acoustic (i.e., sound),vibration, video or still image, motion, smoke detection, chemical,humidity or other sensors, and which could be facing inwards, i.e., intoa room, or outwards, i.e., to the exterior of the room or building, invarious embodiments. The wireless interface 128 has an antenna 124,which is used for coupling to the intelligent windowcontroller/driver(s) 104, the command and communication device 106,and/or one or more user devices 136 (e.g., a smart phone, a userwearable device, etc.). A wired interface 130 could also be included, orcould be used in place of a wireless interface 128. The control system114, shown as the first control system 114 in FIG. 1, provides localcontrol for the electrochromic window 204 via the voltage or currentdriver 208. Alternatively, the control system 114 participates indistributed control. Some embodiments have a rules engine 132 in themodule 206. The voltage or current driver 208 sends voltage or currentto bus bars of the electrochromic window 204, as directed by one or moreof the control systems 114, 116, 118, 120, to control transmissivity ofthe electrochromic window 204. In some embodiments, to changetransmissivity of the electrochromic window 204, the voltage or currentdriver 208 provides constant current until a sense voltage of theelectrochromic window 204 is reached. Then, the voltage or currentdriver 208 provides a current that maintains the sense voltage at aconstant voltage, until a total amount of charge is transferred to theelectrochromic window 204 for the new transmissivity level. The embeddedmodule 206 also includes an input device 214, or a user I/O module 142,through which user input can be entered at the smart window 102. In someembodiments, user input can also be entered through the wirelessinterface 128, e.g., from a smart phone.

FIG. 3 is a system diagram of an intelligent window controller/driver104, from the smart window system of FIG. 1. The intelligent windowcontroller/driver 104 includes a wireless interface 128 with an antenna124, a wired interface 130, a user I/O module 142, and a control system116, which is shown as the second control system 116 in FIG. 1. Someembodiments have a rules engine 132. The wireless interface 128 couplesto one or more smart windows 102 via the wireless interface 128, asshown in FIG. 1, although the wired interface 130 could be used infurther embodiments. Either the wireless interface 128 or the wiredinterface 130 can be used to couple to the command and communicationdevice 106, in various embodiments. In some embodiments, the wirelessinterface 128 and/or the wired interface 130 can couple to furtherdevices, such as third-party devices for input information, sensing orcontrol output. For example, the system could control or interact withlighting controllers, HVAC (heating, ventilation and air-conditioning,e.g., by coupling to a thermostat), burglar and/or fire alarm systems,smart phones, or other systems or devices, or receive further input fromfurther sensors, cameras, etc. The user I/O module 142 could includebuttons, a touchpad, a touchscreen, a display screen, etc., for userinput to the system and/or output from the system. The second controlsystem 116 participates in distributed control with the first controlsystem 114 of the smart window 102, or can override the first controlsystem 114. In some embodiments, the second control system 116 relaysdirection from the third control system 118 of the command andcommunication device, or the fourth control system 120 of the server108, to one or more smart windows 102.

FIG. 4 is a system diagram of a command and communication device 106,from the smart window system of FIG. 1. Since the command andcommunication device 106 is coupled to the network 110, in someembodiments the command and communication device 106 has variousprotections against unauthorized access. Here, the command andcommunication device 106 has a firewall 104, a malware protection engine408, an authentication engine 402, and a certificate repository 406. Thefirewall 104 is applied in a conventional manner, to communicationsarriving via the wired interface 130 or the wireless interface 128 (seeFIG. 1).

The authentication engine 402 can be applied to authenticate anycomponent that is coupled to or desires to couple to the command andcommunication device 106. For example, each smart window 102 could beauthenticated, each intelligent window controller/driver 104 could beauthenticated, and the server 108 could be authenticated, as could anyuser device 136 or other system 138 attempting to access the smartwindow system. The command and communication device 106 can authenticateitself, for example to the server 108. To do so, the command andcommunication device 106 uses a certificate from the certificaterepository 406 for an authentication process (e.g., a “handshake”)applied by the authentication engine 402.

The malware protection engine 408 can look for malware in any of thecommunications received by the commanded communication device 106, andblock, delete, isolate or otherwise handle suspected malware in a mannersimilar to how this is done on personal computers, smart phones and thelike. Updates, e.g., malware signatures, improved malware detectionalgorithms, etc., are transferred to the malware protection engine 408via the network 110, e.g., from the server 108 or one of the othersystems 138 such as a malware protection service.

FIG. 5 is a block diagram showing aspects of the distributed devicenetwork control system architecture of FIG. 1. Although thisarchitecture lends itself to hierarchical control, which is nonethelesspossible and can be performed by overrides from components higher up inthe chain, it should be appreciated that control is generallydistributed across and movable among the first control system(s) 114,the second control system(s) 116, the third control system 118 and thefourth control system 120, i.e., distributed across and movable amongthe server 108, the command and communication device 106, theintelligent window controller/drivers 104, and the smart windows 102.Smart windows 102 can be operated individually, or in various groups(e.g., facing in a particular direction, or associated with a particularroom or group of rooms, or level or floor of a house or other building,subsets or groupings of windows, and so on) using this distributedcontrol architecture. Generally, each control system 114, 116, 118, 120controls or directs one or more of the smart windows 102, in cooperationwith other members of the system. Each control system 114, 116, 118, 120has respective rules, e.g., the first control system 114 has first rules502, the second control system has second rules 504, the third controlsystem 118 has third rules 506, the fourth control system 120 has fourthrules 508. Each control system 114, 116, 118, 120 operates according toits local rules, which may incorporate rules distributed from otherdevices, unless overridden by another device in the system. Rules caninclude cooperation with other devices, and rules can includeinstructions allowing for when an override is permissible. For example,an intelligent window controller/driver 104 could override a smartwindow 102, the command and communication device 106 could override anintelligent window controller/driver 104 or a smart window 102, theserver 108 could override the command and communication device 106, anintelligent window controller/driver 104, or a smart window 102, or userinput at one of the devices or from a user device 136 could override oneor more of these. Information from the sensors 212 of the smartwindow(s) 102 enters the system through the first control system(s) 114,and can be routed or directed to any of the further control systems 116,118, 120. Information 510 from the network enters the system through thefourth control system 120, i.e., the server 108, and/or the thirdcontrol system 118, i.e., the command and communication device 106, andcan be routed or directed to any of the further control systems 114,116. User input can enter the system through the smart windows 102,e.g., through user input at that smart window 102 or wireless user inputfrom a user device 136 to the smart window 102. User input can alsoenter the system through the intelligent window controller/driver(s)104, e.g., through user input at the intelligent windowcontroller/driver 104 or wireless user input from a user device 136.User input can enter the system through the third control system 118,e.g., through a wireless coupling from a user device 136 or via thenetwork connection, e.g., from a user device 136. User input can enterthe system through the fourth control system 120, e.g., via the server108. From any of these entry points, the user input can be routed to anyof the control systems 114, 116, 118, 120. Each of the control systems114, 116, 118, 120 can communicate with each other control system 114,116, 118, 120, and can update respective rules 502, 504, 506, 508 asself-directed or directed by another one or combination of the controlsystems 114, 116, 118, 120. Control can be cooperative, voted, directed,co-opted, overridden, local, distributed, hierarchical, advisory,absolute, and so on, in various combinations at various times duringoperation of the system, in various embodiments.

In some embodiments, the smart window system operates the smart windows102 in a continuous manner, even if there is a network 110 outage (e.g.,there is a network outage outside of the building, a server is down, ora wireless router for the building is turned off or fails, etc.). Thefirst control system 114, the second control system 116 and/or the thirdcontrol system 118 can direct the smart windows 102 without informationfrom the network, under such circumstances. In various combinations,each of the control systems 114, 116, 118, 120 can create, store, shareand/or distribute time-bound instructions (e.g., instructions with goalsto perform a particular action at or by a particular time), and thesetime-bound instructions provide continuity of operation even when one ormore devices, or a network, has a failure. When the network 110 isavailable, the third control system 118 obtains weather information fromthe network, either directly at the third control system 118 or withassistance from the server 108. For example, the third control system118 could include and apply cloud-based adaptive algorithms. With these,the third control system 118 can then direct operation of the smartwindows 102 based on the weather information. One or a combination ofthe control systems 114, 116, 118, 120 can direct operation of the smartwindows 102 based on sensor information, such as from light, image,sound or temperature sensors of the smart windows 102. For example, ifthe weather information indicates cloud cover, or sensors 212 arepicking up lowered light levels, the system could direct an increase intransmissivity of the smart windows 102, to let more natural light in tothe building. If the weather information indicates bright sun, orsensors 212 are picking up increased or high light levels, the systemcould direct a decrease in transmissivity of the smart windows 102, todecrease the amount of natural light let in to the building. The systemcan modify such direction according to orientation of each window, sothat windows pointing away from the incidence of sunlight are directeddifferently than windows pointing towards incidence of sunlight. Ifweather information indicates sunlight, and temperature sensors indicatelow temperatures, the system could direct increased transmissivity ofthe smart windows 102, in order to let in more natural light andincrease heating of a building interior naturally. Or, if thetemperatures sensors indicate high temperatures, the system could directdecreased transmissivity of the smart windows 102, to block naturallight and thereby hold down the heating of the interior of the buildingby sunlight.

FIGS. 6A-6F illustrate various models and a comparison engine, some orall of which could be used in various combinations in embodiments of thesmart window system. Each of these embodiments could be placed invarious locations in the smart window system, as further discussed belowwith reference to FIG. 6F.

FIG. 6A shows aspects of a building model 602 that can be used inembodiments of the smart window system. The building model 602represents placement of each of the smart windows 102 in a particularinstallation of a window system, e.g., in a house or building. Some orall of the aspects shown in FIG. 6A, or further aspects or variationsthereof, could be present in a specific building model 602. Windoworientation 616 could be represented by compass bearing of each smartwindow 102, or positioning or location information for each smart window102 relative to the building in which the smart window 102 is installed.This could be automatically determined based on information from one ormore sensors 212 of the smart window, or by user entry of informationsuch as a floor plan of the building or other information allowing thesystem to deduce the window orientation 616. Window height 604 could bededuced or user entered. County information 606 could be obtained fromthe network 110, and indicate location and orientation information forthe entire building, or building plans, etc. Internet real estate sitesmay provide information 608 from the network 110, and indicate locationinformation for the building. House orientation 610 could be mapped onsite, user entered, deduced from sensor information obtained from thesmart windows 102, or obtained from a smart phone application.Microclimate information 612 could be obtained from the network 110.Some embodiments of smart window systems contribute sensor informationfrom the smart windows 102 to the server 108 (see FIG. 1), which thentracks microclimate weather and makes this information available back tosmart window systems or others (e.g., subscribers or services). Censusinformation 614 could be obtained from the network 110 and give locationinformation for the building or occupant counts for the building, whichcould then be used for establishing the number of user profilesapplicable to an installation of smart windows 102. Other sources andtypes of information could feed into the building model 602. Forexample, online map and photographic information could be used toestablish relative locations and orientations of various smart windows102 (or of windows prior to retrofitting with smart windows 102).

FIG. 6B shows aspects of a shade model 640 that can be used inembodiments of the smart window system. The shade model 640 representsaspects of shade (e.g., blocking of sunlight) affecting each smartwindow 102, groups of smart windows 102 (e.g., the smart windows 102 onthe first story of a three-story building, or smart windows 102 facingin one direction), or the smart windows 102 of an entire building (e.g.,with other buildings, nearby mountains or hills that could shade theentire building). It is not necessary that the shade model 640 representthe source of the shade (i.e., the shade model 640 does not need to knowthat it is a tree, a hillside or another building that is producingshade at a particular time of day for a particular window), althoughsome embodiments could provide entry for such information. Someembodiments deduce the shade model 640 for each smart window 102, orgroup of smart windows 102, based on smart window light sensorsinformation 638. Weather data 618 could be included in the shade model640, as could real-time satellite image/cloud cover information 620 andsun azimuth information 622. With these sources of information, asobtained from the network 110 (e.g., the Internet), the smart windowsystem can deduce whether the sun ought to be shining brightly on awindow, but is not, in which case at that time of day and season underthat weather condition, there could be shade on the smart window 102.Surface images 624 from an Internet map application could be used toprovide information for the shade model 640. Smart phone applicationwindow images 626 could be input into the system, which could thendeduce which windows are shaded at the time that the image was captured.GPS (global positioning system) and compass direction information 628could be input to the system, for example from a smart phone with a GPSand compass function, or other instrument or device, or manuallyentered. This information is useful for determining orientation of awindow 102 and incidence of sunlight relative to that smart window 102,whereupon the shade model 640 can deduce whether shade is affecting thatsmart window 102. Irrigation controllers or rain sensors information 630could be used to deduce whether locally there is rain and attendantcloud cover, which is causing shade on likely all of the smart windows102 of an installation. A smart phone light sensor 632 could provideinput to the shade model 640, operating effectively as a light meter(e.g., deduced from an image capture or live image camera), so that thesystem can deduce when less light is incident on or passing through awindow 102 than ought to be with direct sun shining, in which case thereis shade, and so on. Thermostat information 634 could be used to deducewhether overall the room or building is receiving more or less incidentsunlight than expected according to the weather data 618 or otherrelevant source of information about sunlight, and thereby deduce shadeinformation. Indoor lights information 636 could be used to deducewhether overall the room or building is receiving more or less incidentsunlight than expected, etc. Various single sources or combinations ofthe above sources of information are used in various embodiments toproduce, update or modify the shade model 640.

FIG. 6C shows aspects of a temperature model 656 that can be used inembodiments of the smart window system. The temperature model 656represents the temperature, and influences on the temperature, of one ormore rooms or the entire building in which a window system is installed.Thermostat information 634 could be used to determine whether theuser-intended (or desired) temperature for the inside of the room, houseor building is higher or lower than might be naturally obtained orotherwise expected or predicted, or higher or lower than the indoortemperature as measured by the thermostat 634. For example, regionalinformation 658 (e.g. whether information), local information 642 (e.g.,microclimate information), outdoor house information 646 (e.g., fromoutward facing temperature sensors of smart windows 102 or othersources), and indoor house information 648 (e.g., from inward facingtemperature sensors of smart windows 102 or other sources) can all beprocessed and compared, so that the temperature model 656 deduceswhether the temperature is relatively low or high. The system can thenmake decisions as to whether transmissivity of specific smart windows102, or all of the smart windows 102, should be increased or decreasedto let more or less sunlight in, and to raise, lower or prevent fromraising the indoor temperature as a result. Neighbor information 650could be input to the temperature model 656, particularly whereneighbors are using a smart window system which communicates with theserver 108. Forecast information 652 can be applied to the temperaturemodel 656, so as to make adjustments to transmissivity settings of smartwindows 102 in advance of changes in weather. For example, if a coolingtrend is predicted, the system might decide to increase transmissivityof the smart windows 102, to let more sunlight in and heat up theinterior of the building. If a warming trend is predicted, the systemmight decide to decrease transmissivity of the smart windows 102, todecrease the amount of sunlight let in and avoid heating up the interiorof the building.

FIG. 6D shows a light and comfort model 672 that can be used inembodiments of the smart window system. The light and comfort model 672represents light levels in the interior of a room or building, andvarious influences on the light levels. User behaviors 674 are used bythe light and comfort model 672 to understand when a user manuallyadjusts a smart window 102, enters preference information, or otherwiseinfluences settings or adjustments of the system. A remote lightdetector 660, such as the smart phone light sensor 632, or another userdevice, could be used to independently measure light levels in a room orbuilding. Smart phone light detection 662, such as the smart phone lightsensor 632 could also be used to measure light levels in a room orbuilding. Lighting control information 664, such as could be availablewhen the smart window system includes a lighting controller or couplesto a lighting controller, could be used by the system to observe whenartificial lighting (i.e., not sunlight-based) is applied to theinterior of a room or building. Shade control information 666, such ascould be available when the smart window system includes or couples to ashade control device (see, e.g., FIG. 11), could be used by the systemto observe when shade is deliberately applied to the interior of a roomor building. Adjustment to HVAC (heating, ventilation or airconditioning) information 668 could be used by the system to observewhen an occupant desires warmer or cooler temperatures. Adjustment tolearned modes information 670 could be used by the system to deduce whenthey learned mode setting produced too much or too little natural (i.e.,sunlight-based) light in a room or building. The system can use thelight and comfort model 672 when determining whether to increase ordecrease transmissivity of smart windows 102, to let more or less lightin.

FIG. 6E shows a comparison engine 682 that can be used in embodiments ofthe smart window system. The comparison engine 682 can take presentbuilding information 684 (e.g., as applied to a specific smart windowsystem), and other buildings information 676, and compare models,operation, user preferences, system performance, and other aspects ofsmart window systems from one installation to another. From the presentbuilding information 684 and the other buildings information 676, thecomparison engine 682 can derive smart window “recipes” 678 (e.g., rulessets applicable to smart window systems). The system could also make useof smart window history data 680, for short, medium or long-termcomparisons.

FIG. 6F shows the building model 602 of FIG. 6A in the distributeddevice network 690 of FIGS. 1 and 5, which could also include some orall of the models 640, 656, 672 of FIGS. 6B-6D and the comparison engine682 of FIG. 6E, in various embodiments. Here, the building model 602 isshown as including the shade model 640, as will be further discussedwith reference to FIG. 7. The distributed device network 690 residespartially local 686 to the building in which the smart windows 102 areinstalled, and partially in the cloud 688, in some embodiments.Referring back to FIG. 1, the first, second and third control systems114, 116, 118 are local 686 to the building in which the smart windows102 reside, and the fourth control system 120 is cloud-based, morespecifically, located in the server 108 which is coupled to the network110. The distributed device network 690 holds the building model 602,which can thus also be distributed across multiple control systems 114,116, 118, 120 in the system. Conceptually, a portion of the buildingmodel 602 is generated and maintained locally, and a portion of thebuilding model 602 is cloud-based. Local portion 686 influences to thebuilding model 602 include installer and user feedback 692, and thebuilding floor plan 654 or other information used to represent smartwindow 102 placement. Cloud portion 688 influences to the building model602 include weather prediction data 694, current weather data 696, andhistoric weather data 698 (which could be seasonal or geographic orboth).

FIG. 7 depicts a data structure 702 suitable for holding the buildingmodel 602 and other models 640, 656, 672 and comparison engine 682 ofFIGS. 6A-6F in the distributed device network 690 with smart windows102. The data structure 702 could have various fields 704, 706, 708,712, 714 for various types of information. A building location field 706holds latitude, longitude, GPS, ZIP Code and/or other building locationinformation. The building model 602 has a window information field 704.In the example data structure 702 shown, each smart window 102 isnumbered or otherwise identified, and the direction in which the smartwindow 102 is facing, the story in which the smart window 102 islocated, a shade constraint, a glare constraint, a room designation, andgeneral (e.g., as user entered or deduced by the system) and personal(e.g., per user, as user entered or deduced by the system) preferencesare represented in the window information field 704. There are manyformats and ways in which this or other information, or variationsthereof could be represented, as readily devised by the person of skillin the art. Information could be represented for individual smartwindows 102, or groups, etc. A building information field 708 hasinformation for the front, back, and each side of the building, such aswhich direction each wall is facing, how many stories are on that wall(e.g., a split level house could have one story for the back of thebuilding, two stories for the front of the building and a split one andtwo stories for the sides of the building). An adjustment field 712shows whether the day and night function is adjusted for latitude andseasons, whether weather report monitoring is on or off and whetherlocal microclimate adjustments are on or off. For example, some userswould prefer a clock-based schedule that does not vary per season, andothers would prefer seasonal adjustments to the settings of the system.Some users would prefer to ignore the weather, others would rather thesystem compensate the settings for the weather. Further model fields 714represent the shade model 640, the temperature model 656, and thelighting model 710, by room, by the smart windows 102 per room, and/orthe building overall.

FIG. 8 is a system diagram of the server 108 of FIG. 1, with variousmodules and repositories, as suitable for use with smart window systems.This is one embodiment, and variations with fewer, more, or differingcombinations of features are readily devised. A building modelsrepository 804 is where building models 602 are stored, in single oraggregate form. For example, a smart window system could store a localbuilding model 602 in one of, or distributed across, the first controlsystem 114, the second control system 116 and the third control system118, with a duplicate copy of the local building model 602 stored in thebuilding models repository 804 of the server 108 as part of the fourthcontrol system 120 (see FIGS. 1 and 5). Or, each smart window systemcould have the building model 602 distributed across local componentsand the server 108. A user profiles repository 806 is where userprofiles are stored in the server 108. Each of these is updated, revisedor modified on an ongoing basis, which could be at regular or irregulartime intervals or responsive to changes, etc.

A recommendation engine 810 generates smart window recipes 678 (see FIG.6E), and stores these in a smart window recipes repository 812. Therecipes 678 could include personal comfort models, energy efficiencymodels, preference models, profiles of smart window operation, etc. Asocial networking service 808 can gather smart window recipes 678 asshared by users of smart window systems, and store these in or accessthese for sharing from the smart window recipes repository 812. Amicroclimate tracker 814 receives sensor information from smart windows102 of multiple smart window systems, and tracks microclimate based onthe sensor information. Microclimate weather information could be madeavailable by the server 108, to other systems or subscribers (e.g., fora subscription fee).

An energy usage and smart window usage tracker 816 communicates withutilities or building systems (e.g. HVAC) and tracks energy usage, andalso tracks usage of smart window systems 802 that are coupled to theserver 108 via the network 110. From this, the energy usage and smartwindow usage tracker 816 can generate recommendations 818, for exampleof smart window recipes 678 from the smart window recipes repository812. This could make use of the comparison engine 682 (of FIG. 6E). Theenergy usage and smart window usage tracker 816 can also generate energyaudits 820, which could accompany recommendations 818.

A thermal resistance R value/U factor calculator 822 looks attemperature differences inside and outside of a room or building, basedon sensor information from sensors 212 of the smart windows 102, andpossibly also based on communication with HVAC systems or thermostatinformation 634. Then, the thermal resistance R value/U factorcalculator 822 calculates (e.g., estimates) the thermal resistance(e.g., the R value) or its inverse, the thermal transmittance (e.g., theU factor).

A report generator 824 could generate reports of various aspects ofsystem operation, such as which smart windows 102 have frequent manualadjustments, or which smart windows 102 are allowed to self-adjustwithout much manual adjustment. The report generator 824 could reportwhich smart windows 102, or how many smart windows 102, have operationconsistent with a recommendation based on the shade model 640, or reporta ratio of the number of smart windows 102 that have such operation ascompared to the number of smart windows 102 that have operationinconsistent with the recommendation. A report could include arecommendation, based on a finding that some of the smart windows 102are operated in a manner that is less energy efficient. Other types ofreports are readily devised.

A building appearance simulator engine 826 renders images of buildingswith smart windows 102, to show how a building would appear with changesto transmissivity settings of the smart windows 102. This could beaccomplished by having the server 108 receive a captured image, orvideo, of a building that has smart windows 102. For example, a usercould use a camera of a smart phone or other user device 136, and send apicture of a building to the server 108 via the network 110. The servercould then coordinate with the appropriate (i.e., corresponding) one ofthe building models 602 in the building models repository 804, or usepattern recognition or other computing technique, to identify windows inthe captured image or video. A user communicating with the server 108,for example via a user device 136 and the network 110, could use atouchscreen or cursor manipulation to indicate a selection of one ormore smart windows 102 in the image, and then indicate a new setting ora pattern for one or more smart windows 102. The building appearancesimulator engine 826 would then render an image simulating theappearance of the building with the new transmissivity settings for thesmart windows 102. This simulated appearance rendered image could betermed a type of “augmented reality” depiction. In some embodiments, theuser device 136 communicates to the smart window system (e.g., aspecific installation at a specific building), and directs the smartwindow system to set transmissivity of specific smart windows 102 inaccordance with the rendered image, thereby reproducing the simulatedappearance of the building in the actual appearance of the building withthe smart windows 102. An example of this is shown and described withreference to FIG. 14.

FIG. 9 is a system diagram of the distributed device network 690 ofFIGS. 1, 5 and 6F interacting with smart windows and lights, in acooperative system with voting and visual representation for users of asmart window system. Some or all of the aspects of this embodiment areavailable in further embodiments, in various combinations. Thedistributed device network 690 couple to and communicates with, orintegrates one or more lighting controller(s) 104, which couple tovarious lights 906. As described above, the smart window system, e.g.the distributed device network 690, operates the smart windows 102 basedon input from the sensors 212, information from the network 110, andvarious user inputs 902. In this embodiment, the system votes on userinputs 902, using voting 908. Various voting schemes or mechanisms couldbe implemented using one or more of the control systems 114, 116, 118,120 of the distributed device network 690. Based on results of thevoting 908, the system sets transmissivity of one or more smart windows102 and/or sets lighting levels of one or more lights 906. One goal ofsuch a system would be to achieve an overall combination of naturallighting and artificial lighting that is preferred by a majority of theusers, per the voting 908. Voting 908 could also be applied inembodiments with the building appearance simulator engine 826 describedwith reference to FIG. 8 and/or the pattern displays described belowwith reference to FIG. 14. To guide the users who are directing lightinglevels or building appearance using the voting 908, the system couldemploy the building appearance simulator engine 826 to generate a visualrepresentation 910 showing an interior or exterior simulated appearancebased on either an individual requested setting for selected smartwindows 102, or the voted setting for selected smart windows 102. Thisvisual representation 910 (e.g., a rendered image in an appropriateimage format) could be sent by the system to any of the user devices136, or, in embodiments of the smart window system with one or moredisplays (e.g., on an intelligent window controller/driver 104 or thecommand and communication device 106), a system device could display thevisual representation 910.

FIG. 10 shows an embodiment of a smart window 102 with transmissivitygradation. The electrochromic window 204 in this embodiment has multiplezones, each controllable independently of others as to transmissivity.For example, zones could be bounded by bus bars, with voltage betweenbus bars of a zone, or current through bus bars of a zone, controllingtransmissivity of that zone of electrochromic material. Or, theelectrochromic window 204 could have multiple panes, with each paneindependently controllable as to transmissivity. In the example shown,the uppermost zone or pane is set to low or minimum transmissivity, andsuccessive zones or panes are set to higher transmissivity, with thelowermost zone or pane set to still higher or maximum transmissivity, sothat the lower portions of the smart window 102 let in more light orview than the upper portions of the smart window 102. This is useful forletting in light without dazzling or blinding a user who is seated nearthe smart window 102, e.g., at a desk or table, who wishes naturallighting for the desk, table or other surroundings, but less sunlightinto his or her eyes. In this example, the zones or panes are laid outhorizontally, but further embodiments could have vertical or diagonallayouts for zones or panes, or curved layouts (e.g. circular, oval, halfcircle, half oval, and so on).

FIG. 11 shows an embodiment of a smart window 102 with a motorizedwindow blind 1102 and motorized opening and closing. Generally, smartwindows 102 could have multiple features besides of electrochromicwindows 204, and this embodiment shows two possibilities. A first motor1106 operates the window blind 1102 up and down, under control of theembedded module 206 (see FIG. 2) specifically, and the distributeddevice network 690 generally. Further embodiments could have a windowblind operated from side to side, or at other angles, or motorizeddrapes, shutters, etc., as shade control. A second motor 1108 operatesthe electrochromic window 204 to swing open and closed, or,alternatively, up and down or in and out, or with a two pane splitopening outwards or inwards and closing, etc. This, too, is controlledby the embedded module 206 and the distributed device network 690. Invarious scenarios, a smart window system could control opening andclosing of smart windows 102 for natural ventilation and/or couldcontrol window blinds 1102 or related features along with controllingtransmissivity of smart windows 102, for user comfort.

FIG. 12 shows an embodiment of a smart window 102 with an auto-tint 1204function. As in other embodiments, the smart window 102 has one or moresensors 212. In this scenario, the sensor(s) 212 receive light and/orsound from a nearby television 1202 in operation. The smart windowsystem deduces that the television 1202 is on (e.g., by looking for theflicker of light or the variety of sounds associated with televisionoperation, or by processing a captured or video image from a camera as asensor 212), and determines which smart window 102 is nearest thetelevision 1202 (e.g., by comparing sound levels or light levels fromsensors 212 of smart windows 102, or processing images). Next, the smartwindow system directs that nearest smart window 102, or a group of smartwindows 102 (e.g., assigned to a specific room), to decreasetransmissivity. With this action, the auto-tint 1204 function reducessunlight glare and overall natural light levels in the vicinity of thetelevision 1202, for more pleasant viewing. The auto-tint 1204 functioncould be applied in further scenarios, such as with the system detectingvarious user activities.

FIG. 13 shows an embodiment of a smart window system with voice controland a nearest window location function. A smart phone or other userdevice 136 is communicating with the smart window system, for example bywirelessly coupling to an intelligent window controller/driver 104 orthe command and communication device 106. The smart phone or other userdevice 136 has speech recognition, and recognizes a user givingdirections such as to dim the nearest smart window 102. Alternatively,sensors 212 of smart windows 102 receive sound from a user, and anembodiment of the smart window system could have speech recognitionbuilt-in. By comparing sound levels at multiple smart windows 102, basedon input from the sensors 212, the smart window system deduces whichsmart window 102 is closest to the user who is speaking, and directsthat smart window 102 to decrease transmissivity as directed by theuser. Voice control and the nearest window location function can beapplied to other voice commands, such as brightening the nearest window,dimming or brightening all the windows in the room, multiple rooms orthe entire building, or use of other phrases and instructions relevantto the smart windows 102.

FIG. 14 depicts a building with a smart windows pattern 1402. In variousembodiments, all of the smart windows 102 of an entire building areunder control of a single distributed device network 690 (see FIGS. 1, 5and 9), or multiple distributed device networks 690 couple together,e.g., via the network 110 and communicate amongst themselves. One ormore users, singly, or with voting 908 as described with reference toFIG. 9, or with another cooperative mechanism, to display on thebuilding exterior (or, in some embodiments, interior). For example,users communicate a pattern with user devices 136. The distributeddevice network(s) 690 direct each of the smart windows 102, e.g., of oneface of the building, or all faces, etc., to change transmissivity inaccordance with the pattern 1402, and the exterior of the building showsthe pattern 1402 as depicted in FIG. 14. In some embodiments, the smartwindow system communicates a visual representation 910 (see FIG. 9) ofthe building with the pattern 1402, as generated by the buildingappearance simulator engine 826 (see FIG. 8), to one or more userdevices 136. Many patterns 1402 are possible, and patterns 1402 could bedeveloped, shared, e.g. through a social networking service 808 (seeFIG. 8), and displayed for special events, holidays, different times ofthe day or day to day, etc. The specific pattern 1402 shown is byexample only, and should not be seen as limiting.

FIG. 15 is a flow diagram of a method of operating a smart windowsystem. The method can be practiced by embodiments of the smart windowsystem, more specifically by one or more processors of a smart windowsystem or a distributed device network that includes smart windows. Inan action 1502, sensor information is received from sensors of the smartwindow system. These could be sensors embedded in the smart windowsand/or sensors coupled to intelligent window controller/drivers. Varioustypes of sensors are possible. In an action 1504, information isreceived from a network. This could be the global communication networkknown as the Internet, and could include sample profiles, weatherinformation, seasonal or geographic information, etc. In an action 1506,a building model is generated. In an action 1508, shade modeling isdeveloped. The building model and the shade modeling are based on thesensor information and the information received from the network. Othermodels are possible.

In an action 1510, smart windows are controlled based on the buildingmodel. Control of the smart windows is also based on sensor information,user input and information from the network. In an action 1512, thebuilding model is revised or updated. Revision or updating of thebuilding model is based on sensor information, user input andinformation from the network. This can be an ongoing process, or couldbe event driven or scheduled, etc. Flow proceeds back to the action1510, to control the smart windows and revise or update the buildingmodel, in a loop. It should be appreciated that further actions could beadded to the method, to add further features or refine actions with moredetail, or branch to various routines, etc.

It should be appreciated that the methods described herein may beperformed with a digital processing system, such as a conventional,general-purpose computer system. Special purpose computers, which aredesigned or programmed to perform only one function may be used in thealternative. FIG. 16 is an illustration showing an exemplary computingdevice which may implement the embodiments described herein. Thecomputing device of FIG. 16 may be used to perform embodiments of thefunctionality for the smart window system in accordance with someembodiments. The computing device includes a central processing unit(CPU) 1601, which is coupled through a bus 1605 to a memory 1603, andmass storage device 1607. Mass storage device 1607 represents apersistent data storage device such as a floppy disc drive or a fixeddisc drive, which may be local or remote in some embodiments. Memory1603 may include read only memory, random access memory, etc.Applications resident on the computing device may be stored on oraccessed via a computer readable medium such as memory 1603 or massstorage device 1607 in some embodiments. Applications may also be in theform of modulated electronic signals modulated accessed via a networkmodem or other network interface of the computing device. It should beappreciated that CPU 1601 may be embodied in a general-purposeprocessor, a special purpose processor, or a specially programmed logicdevice in some embodiments.

Display 1611 is in communication with CPU 1601, memory 1603, and massstorage device 1607, through bus 1605. Display 1611 is configured todisplay any visualization tools or reports associated with the systemdescribed herein. Input/output device 1609 is coupled to bus 1605 inorder to communicate information in command selections to CPU 1601. Itshould be appreciated that data to and from external devices may becommunicated through the input/output device 1609. CPU 1601 can bedefined to execute the functionality described herein to enable thefunctionality described with reference to FIGS. 1-15. The code embodyingthis functionality may be stored within memory 1603 or mass storagedevice 1607 for execution by a processor such as CPU 1601 in someembodiments. The operating system on the computing device may be MSDOS™, MS-WINDOWS™, OS/2™, UNIX™, LINUX™, or other known operatingsystems. It should be appreciated that the embodiments described hereinmay also be integrated with a virtualized computing system implementedwith physical computing resources.

Detailed illustrative embodiments are disclosed herein. However,specific functional details disclosed herein are merely representativefor purposes of describing embodiments. Embodiments may, however, beembodied in many alternate forms and should not be construed as limitedto only the embodiments set forth herein.

It should be understood that although the terms first, second, etc. maybe used herein to describe various steps or calculations, these steps orcalculations should not be limited by these terms. These terms are onlyused to distinguish one step or calculation from another. For example, afirst calculation could be termed a second calculation, and, similarly,a second step could be termed a first step, without departing from thescope of this disclosure. As used herein, the term “and/or” and the “/”symbol includes any and all combinations of one or more of theassociated listed items.

As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”,“comprising”, “includes”, and/or “including”, when used herein, specifythe presence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof. Therefore, the terminology usedherein is for the purpose of describing particular embodiments only andis not intended to be limiting.

It should also be noted that in some alternative implementations, thefunctions/acts noted may occur out of the order noted in the figures.For example, two figures shown in succession may in fact be executedsubstantially concurrently or may sometimes be executed in the reverseorder, depending upon the functionality/acts involved.

With the above embodiments in mind, it should be understood that theembodiments might employ various computer-implemented operationsinvolving data stored in computer systems. These operations are thoserequiring physical manipulation of physical quantities. Usually, thoughnot necessarily, these quantities take the form of electrical ormagnetic signals capable of being stored, transferred, combined,compared, and otherwise manipulated. Further, the manipulationsperformed are often referred to in terms, such as producing,identifying, determining, or comparing. Any of the operations describedherein that form part of the embodiments are useful machine operations.The embodiments also relate to a device or an apparatus for performingthese operations. The apparatus can be specially constructed for therequired purpose, or the apparatus can be a general-purpose computerselectively activated or configured by a computer program stored in thecomputer. In particular, various general-purpose machines can be usedwith computer programs written in accordance with the teachings herein,or it may be more convenient to construct a more specialized apparatusto perform the required operations.

A module, an application, a layer, an agent or other method-operableentity could be implemented as hardware, firmware, or a processorexecuting software, or combinations thereof. It should be appreciatedthat, where a software-based embodiment is disclosed herein, thesoftware can be embodied in a physical machine such as a controller. Forexample, a controller could include a first module and a second module.A controller could be configured to perform various actions, e.g., of amethod, an application, a layer or an agent.

The embodiments can also be embodied as computer readable code on atangible non-transitory computer readable medium. The computer readablemedium is any data storage device that can store data, which can bethereafter read by a computer system. Examples of the computer readablemedium include hard drives, network attached storage (NAS), read-onlymemory, random-access memory, CD-ROMs, CD-Rs, CD-RWs, magnetic tapes,and other optical and non-optical data storage devices. The computerreadable medium can also be distributed over a network coupled computersystem so that the computer readable code is stored and executed in adistributed fashion. Embodiments described herein may be practiced withvarious computer system configurations including hand-held devices,tablets, microprocessor systems, microprocessor-based or programmableconsumer electronics, minicomputers, mainframe computers and the like.The embodiments can also be practiced in distributed computingenvironments where tasks are performed by remote processing devices thatare linked through a wire-based or wireless network.

Although the method operations were described in a specific order, itshould be understood that other operations may be performed in betweendescribed operations, described operations may be adjusted so that theyoccur at slightly different times or the described operations may bedistributed in a system which allows the occurrence of the processingoperations at various intervals associated with the processing.

In various embodiments, one or more portions of the methods andmechanisms described herein may form part of a cloud-computingenvironment. In such embodiments, resources may be provided over theInternet as services according to one or more various models. Suchmodels may include Infrastructure as a Service (IaaS), Platform as aService (PaaS), and Software as a Service (SaaS). In IaaS, computerinfrastructure is delivered as a service. In such a case, the computingequipment is generally owned and operated by the service provider. Inthe PaaS model, software tools and underlying equipment used bydevelopers to develop software solutions may be provided as a serviceand hosted by the service provider. SaaS typically includes a serviceprovider licensing software as a service on demand. The service providermay host the software, or may deploy the software to a customer for agiven period of time. Numerous combinations of the above models arepossible and are contemplated.

Various units, circuits, or other components may be described or claimedas “configured to” perform a task or tasks. In such contexts, the phrase“configured to” is used to connote structure by indicating that theunits/circuits/components include structure (e.g., circuitry) thatperforms the task or tasks during operation. As such, theunit/circuit/component can be said to be configured to perform the taskeven when the specified unit/circuit/component is not currentlyoperational (e.g., is not on). The units/circuits/components used withthe “configured to” language include hardware—for example, circuits,memory storing program instructions executable to implement theoperation, etc. Reciting that a unit/circuit/component is “configuredto” perform one or more tasks is expressly intended not to invoke 35U.S.C. 112, sixth paragraph, for that unit/circuit/component.Additionally, “configured to” can include generic structure (e.g.,generic circuitry) that is manipulated by software and/or firmware(e.g., an FPGA or a general-purpose processor executing software) tooperate in manner that is capable of performing the task(s) at issue.“Configured to” may also include adapting a manufacturing process (e.g.,a semiconductor fabrication facility) to fabricate devices (e.g.,integrated circuits) that are adapted to implement or perform one ormore tasks.

The foregoing description, for the purpose of explanation, has beendescribed with reference to specific embodiments. However, theillustrative discussions above are not intended to be exhaustive or tolimit the invention to the precise forms disclosed. Many modificationsand variations are possible in view of the above teachings. Theembodiments were chosen and described in order to best explain theprinciples of the embodiments and its practical applications, to therebyenable others skilled in the art to best utilize the embodiments andvarious modifications as may be suited to the particular usecontemplated. Accordingly, the present embodiments are to be consideredas illustrative and not restrictive, and the invention is not to belimited to the details given herein, but may be modified within thescope and equivalents of the appended claims.

What is claimed is:
 1. A smart window system, comprising: a plurality ofsmart windows, each having at least one electrochromic window; aplurality of sensors; a control system coupling the plurality of smartwindows and the plurality of sensors; and the control system configuredto couple to a network, and configured to generate a building model thatincludes information regarding the plurality of smart windows and isbased on a profile of smart window operation received from the networkand wherein the profile is revised based on information from theplurality of sensors, wherein the plurality of smart windows and thecontrol system are configured to have local a first portion of thebuilding model, and wherein a second portion of the building model islocal to at least one server in the network.
 2. The smart window systemof claim 1, wherein the building model is based on environmentalinformation from the network and based on installer or user input. 3.The smart window system of claim 1, wherein the building model includesshade modeling for each smart window of the plurality of smart windows.4. The smart window system of claim 1, wherein the control system isconfigured to control transmissivity of each of the plurality of smartwindows based on the building model.
 5. The smart window system of claim1, wherein the building model is adaptive and is based on a shade modeland weather information.
 6. The smart window system of claim 1, whereinthe building model is based on at least one further building model fromat least one further smart window system.
 7. A smart window system,comprising: a plurality of smart windows, each smart window of theplurality of smart windows having integrated into the smart window atleast one sensor and at least one electrochromic window; a controlsystem that includes the plurality of smart windows and is configured tocouple to a network; the control system, configured to produce abuilding model based on a profile of smart window operation receivedfrom the network and wherein the profile is revised based on informationfrom the at least one sensor or user input, and wherein the buildingmodel includes information regarding placements of the plurality ofsmart windows relative to a building.
 8. The smart window system ofclaim 7, wherein a server in the network is configured to trackmicroclimate weather based on sensor input from a plurality of smartwindow systems, and wherein the building model is based on the trackedmicroclimate weather.
 9. The smart window system of claim 7, furthercomprising: the control system, configured to store the building modelin a data structure that references each smart window of the pluralityof smart windows as to a shade model of the smart window.
 10. The smartwindow system of claim 7, wherein a portion of the building modelresides in the network.
 11. The smart window system of claim 7, whereinthe building model includes at least one of: a shade model, atemperature model, or a lighting model.
 12. The smart window system ofclaim 7, further comprising: the control system, configured to revisethe building model on an ongoing basis.
 13. The smart window system ofclaim 7, further comprising: the control system, configured to comparetemperature or lighting level, based on the information from the sensorsof the plurality of smart windows, to a predicted temperature or apredicted lighting level, based on the building model, and report aresult of such a comparison.
 14. A method of operating a smart windowsystem, performed by one or more processors of the smart window system,comprising: receiving sensor information from sensors of the smartwindow system, wherein the smart window system includes a plurality ofsmart windows with electrochromic windows, and the sensors; receivinginformation from a network; generating, in the smart window system, abuilding model referencing each smart window of the plurality of smartwindows with placement, location or orientation of the smart window,wherein at least a portion of the building model is based on the sensorinformation and the information from the network; receiving, from thenetwork, a profile of smart window operation; basing the building model,at least in part, on the profile of smart window operation; revising thebuilding model, based on one of the sensor information or user input;and controlling each smart window of the plurality of smart windows,based on the building model.
 15. The method of claim 14, furthercomprising: developing shade modeling for the building model, based onthe sensor information and the information from the network.
 16. Themethod of claim 14, further comprising: revising the building modelbased on at least one of: historical weather data, current weather data,and predictive weather data, as received from the network.
 17. Themethod of claim 14, further comprising: receiving, from the network, apersonal comfort model or an energy efficiency model; and updating thebuilding model based on the personal comfort model or the energyefficiency model.
 18. The method of claim 14, sending at least a portionof the sensor information to a server, via the network, wherein theserver is configured to track microclimate weather based on sensorinformation from a plurality of smart window systems; receivingmicroclimate weather information from the server, via the network; andupdating the building model, based on the microclimate weatherinformation.